Overview

Dataset statistics

Number of variables18
Number of observations2410
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory357.7 KiB
Average record size in memory152.0 B

Variable types

DateTime1
TimeSeries15
Numeric2

Timeseries statistics

Number of series15
Time series length2410
Starting point2010-01-26 00:00:00
Ending point2019-08-26 00:00:00
Period1 day, 10 hours and 51 minutes
2026-02-01T18:39:33.478274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:33.771929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

AD is highly overall correlated with EMA and 7 other fieldsHigh correlation
ATR is highly overall correlated with NATR and 2 other fieldsHigh correlation
CMO is highly overall correlated with ROC and 1 other fieldsHigh correlation
EMA is highly overall correlated with AD and 6 other fieldsHigh correlation
KAMA is highly overall correlated with AD and 6 other fieldsHigh correlation
MA is highly overall correlated with AD and 6 other fieldsHigh correlation
MidPrice is highly overall correlated with AD and 6 other fieldsHigh correlation
NATR is highly overall correlated with ATR and 1 other fieldsHigh correlation
OBV is highly overall correlated with AD and 1 other fieldsHigh correlation
ROC is highly overall correlated with CMO and 1 other fieldsHigh correlation
TRANGE is highly overall correlated with ATR and 1 other fieldsHigh correlation
TSF is highly overall correlated with AD and 6 other fieldsHigh correlation
WILLR is highly overall correlated with CMO and 1 other fieldsHigh correlation
WMA is highly overall correlated with AD and 6 other fieldsHigh correlation
close is highly overall correlated with AD and 6 other fieldsHigh correlation
close is non stationaryNon stationary
MA is non stationaryNon stationary
EMA is non stationaryNon stationary
KAMA is non stationaryNon stationary
WMA is non stationaryNon stationary
MidPrice is non stationaryNon stationary
AD is non stationaryNon stationary
OBV is non stationaryNon stationary
NATR is non stationaryNon stationary
ATR is non stationaryNon stationary
TSF is non stationaryNon stationary
close is seasonalSeasonal
MA is seasonalSeasonal
EMA is seasonalSeasonal
KAMA is seasonalSeasonal
WMA is seasonalSeasonal
MidPrice is seasonalSeasonal
AD is seasonalSeasonal
OBV is seasonalSeasonal
NATR is seasonalSeasonal
ATR is seasonalSeasonal
Date has unique valuesUnique
EMA has unique valuesUnique
KAMA has unique valuesUnique
WMA has unique valuesUnique
NATR has unique valuesUnique
ATR has unique valuesUnique
TSF has unique valuesUnique
BOP has 258 (10.7%) zerosZeros
WILLR has 43 (1.8%) zerosZeros

Reproduction

Analysis started2026-02-02 00:39:12.133217
Analysis finished2026-02-02 00:39:33.289849
Duration21.16 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.7 KiB
Minimum2010-01-26 00:00:00
Maximum2019-08-26 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T18:39:33.965489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:34.149526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1854
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1343.0295
Minimum1050.8
Maximum1888.7
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:34.251504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1050.8
5-th percentile1118.435
Q11223.7
median1290.1
Q31407.625
95-th percentile1720.515
Maximum1888.7
Range837.8999
Interquartile range (IQR)183.92508

Descriptive statistics

Standard deviation179.84875
Coefficient of variation (CV)0.13391273
Kurtosis0.053299106
Mean1343.0295
Median Absolute Deviation (MAD)78.950012
Skewness0.98726727
Sum3236701.1
Variance32345.573
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.293181298
2026-02-01T18:39:34.344852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:34.587608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:35.245356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1273.6999516
 
0.2%
1313.6999515
 
0.2%
1291.5999764
 
0.2%
1293.3000494
 
0.2%
1225.3000494
 
0.2%
1251.6999514
 
0.2%
13194
 
0.2%
1294.6999514
 
0.2%
1324.6999514
 
0.2%
1253.8000494
 
0.2%
Other values (1844)2367
98.2%
ValueCountFrequency (%)
1050.8000491
< 0.1%
1052.1999511
< 0.1%
1054.1999511
< 0.1%
1056.1999511
< 0.1%
1060.0999761
< 0.1%
1060.3000491
< 0.1%
1061.6999511
< 0.1%
1062.4000241
< 0.1%
1062.9000241
< 0.1%
1063.8000491
< 0.1%
ValueCountFrequency (%)
1888.6999511
< 0.1%
1873.6999511
< 0.1%
1869.9000241
< 0.1%
1858.3000491
< 0.1%
1856.4000241
< 0.1%
1854.4000241
< 0.1%
1848.9000241
< 0.1%
1828.51
< 0.1%
1826.8000491
< 0.1%
1826.6999511
< 0.1%
2026-02-01T18:39:34.424889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2383
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.28
Minimum1066.77
Maximum1838.65
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:35.608479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1066.77
5-th percentile1117.563
Q11223.79
median1291.295
Q31398.35
95-th percentile1719.9665
Maximum1838.65
Range771.87999
Interquartile range (IQR)174.55999

Descriptive statistics

Standard deviation179.10395
Coefficient of variation (CV)0.13343263
Kurtosis0.021822608
Mean1342.28
Median Absolute Deviation (MAD)78.840009
Skewness0.98906547
Sum3234894.7
Variance32078.224
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4677410783
2026-02-01T18:39:35.808373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:36.057658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:36.706976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1229.389992
 
0.1%
1398.3499882
 
0.1%
1236.8599982
 
0.1%
1067.4200072
 
0.1%
1203.8799932
 
0.1%
1070.9200072
 
0.1%
1259.810012
 
0.1%
1292.7099982
 
0.1%
1279.0000122
 
0.1%
1197.7400022
 
0.1%
Other values (2373)2390
99.2%
ValueCountFrequency (%)
1066.7700071
< 0.1%
1067.4200072
0.1%
1067.4800171
< 0.1%
1068.3700071
< 0.1%
1068.71
< 0.1%
1068.8700071
< 0.1%
1068.9300171
< 0.1%
1068.9599981
< 0.1%
1069.6400021
< 0.1%
1069.8700071
< 0.1%
ValueCountFrequency (%)
1838.651
< 0.1%
1838.3300051
< 0.1%
1834.8099981
< 0.1%
1833.3300051
< 0.1%
1833.2299931
< 0.1%
1831.9400021
< 0.1%
1823.5699951
< 0.1%
1822.210011
< 0.1%
1819.8299931
< 0.1%
1817.951
< 0.1%
2026-02-01T18:39:35.891536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

EMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.2948
Minimum1066.7509
Maximum1835.3699
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:37.202499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1066.7509
5-th percentile1117.6645
Q11223.6105
median1291.0055
Q31397.7595
95-th percentile1719.1343
Maximum1835.3699
Range768.61902
Interquartile range (IQR)174.14906

Descriptive statistics

Standard deviation178.68313
Coefficient of variation (CV)0.13311765
Kurtosis0.00040675311
Mean1342.2948
Median Absolute Deviation (MAD)77.412322
Skewness0.9879778
Sum3234930.4
Variance31927.66
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.321133288
2026-02-01T18:39:37.302178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:37.551588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:38.186844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1111.4576791
 
< 0.1%
1106.5381061
 
< 0.1%
1102.3675371
 
< 0.1%
1098.8461661
 
< 0.1%
1099.8377811
 
< 0.1%
1103.0309161
 
< 0.1%
1104.5525721
 
< 0.1%
1096.8884731
 
< 0.1%
1088.7632871
 
< 0.1%
1084.5699531
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
1066.7508561
< 0.1%
1067.6741931
< 0.1%
1067.873281
< 0.1%
1068.0018031
< 0.1%
1068.5987131
< 0.1%
1069.7807611
< 0.1%
1069.9779731
< 0.1%
1070.2607081
< 0.1%
1070.4428611
< 0.1%
1070.4520621
< 0.1%
ValueCountFrequency (%)
1835.3698731
< 0.1%
1830.7389911
< 0.1%
1830.6965061
< 0.1%
1830.022821
< 0.1%
1828.8368531
< 0.1%
1827.9244151
< 0.1%
1825.4290581
< 0.1%
1819.6846981
< 0.1%
1818.5965011
< 0.1%
1818.3056571
< 0.1%
2026-02-01T18:39:37.385382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

KAMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1343.1664
Minimum1071.6528
Maximum1818.3011
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:38.680192image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1071.6528
5-th percentile1112.1432
Q11221.4794
median1292.6212
Q31401.8774
95-th percentile1720.6661
Maximum1818.3011
Range746.64826
Interquartile range (IQR)180.39799

Descriptive statistics

Standard deviation180.45418
Coefficient of variation (CV)0.13434984
Kurtosis-0.028617661
Mean1343.1664
Median Absolute Deviation (MAD)78.582296
Skewness0.97893942
Sum3237031
Variance32563.713
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3148459878
2026-02-01T18:39:38.783921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:39.037964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:39.699631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1120.6544041
 
< 0.1%
1117.1369871
 
< 0.1%
1112.3747011
 
< 0.1%
1106.7503071
 
< 0.1%
1106.6396911
 
< 0.1%
1107.021121
 
< 0.1%
1107.0430321
 
< 0.1%
1104.1093721
 
< 0.1%
1100.9844341
 
< 0.1%
1099.5670371
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
1071.6528171
< 0.1%
1071.760361
< 0.1%
1071.8025671
< 0.1%
1071.8050121
< 0.1%
1071.8241381
< 0.1%
1071.9016291
< 0.1%
1071.9141461
< 0.1%
1071.9374321
< 0.1%
1071.9474141
< 0.1%
1071.9555721
< 0.1%
ValueCountFrequency (%)
1818.3010761
< 0.1%
1818.2730241
< 0.1%
1818.1513271
< 0.1%
1818.0629781
< 0.1%
1817.0296151
< 0.1%
1816.9870541
< 0.1%
1813.9894551
< 0.1%
1813.9309281
< 0.1%
1813.7287541
< 0.1%
1813.6691611
< 0.1%
2026-02-01T18:39:38.868110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1342.5213
Minimum1063.5255
Maximum1843.5218
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:40.293307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1063.5255
5-th percentile1116.3345
Q11224.1659
median1290.9536
Q31401.7823
95-th percentile1719.1016
Maximum1843.5218
Range779.99636
Interquartile range (IQR)177.61634

Descriptive statistics

Standard deviation179.21099
Coefficient of variation (CV)0.13348838
Kurtosis0.024662551
Mean1342.5213
Median Absolute Deviation (MAD)78.681836
Skewness0.98767771
Sum3235476.3
Variance32116.579
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.30221333
2026-02-01T18:39:40.396984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:40.657402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:41.328606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1108.9181641
 
< 0.1%
1102.8999891
 
< 0.1%
1097.5454411
 
< 0.1%
1093.0418081
 
< 0.1%
1093.4945471
 
< 0.1%
1096.7981891
 
< 0.1%
1099.4163751
 
< 0.1%
1093.1418351
 
< 0.1%
1085.7454611
 
< 0.1%
1081.4763611
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
1063.5254531
< 0.1%
1064.5763741
< 0.1%
1066.7490881
< 0.1%
1067.2545681
< 0.1%
1067.4618161
< 0.1%
1068.3818181
< 0.1%
1068.538191
< 0.1%
1068.5491061
< 0.1%
1069.0127331
< 0.1%
1069.5727291
< 0.1%
ValueCountFrequency (%)
1843.5218151
< 0.1%
1839.2800031
< 0.1%
1837.8236481
< 0.1%
1837.5527191
< 0.1%
1835.0691031
< 0.1%
1830.8054491
< 0.1%
1830.1236221
< 0.1%
1824.190921
< 0.1%
1823.3727321
< 0.1%
1821.7018071
< 0.1%
2026-02-01T18:39:40.481872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MidPrice
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1402
Distinct (%)58.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.8117
Minimum1064.55
Maximum1852.2
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:41.835652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1064.55
5-th percentile1119.3675
Q11223.1125
median1292.05
Q31399.4875
95-th percentile1715.9975
Maximum1852.2
Range787.65002
Interquartile range (IQR)176.37494

Descriptive statistics

Standard deviation178.09249
Coefficient of variation (CV)0.13272539
Kurtosis0.027738729
Mean1341.8117
Median Absolute Deviation (MAD)79.474976
Skewness0.9861511
Sum3233766.3
Variance31716.935
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.2810420556
2026-02-01T18:39:41.936733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:42.194636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:42.869471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1239.95001210
 
0.4%
1308.20001210
 
0.4%
1067.59
 
0.4%
1225.2999888
 
0.3%
1322.7999888
 
0.3%
1659.758
 
0.3%
13268
 
0.3%
1224.57
 
0.3%
13037
 
0.3%
1252.2999887
 
0.3%
Other values (1392)2328
96.6%
ValueCountFrequency (%)
1064.5499881
 
< 0.1%
1066.2000122
 
0.1%
1066.251
 
< 0.1%
10671
 
< 0.1%
1067.59
0.4%
1068.252
 
0.1%
1068.51
 
< 0.1%
1069.6500241
 
< 0.1%
1071.752
 
0.1%
1074.6500244
0.2%
ValueCountFrequency (%)
1852.2000121
 
< 0.1%
1847.3499762
 
0.1%
1843.7000121
 
< 0.1%
1840.0499883
0.1%
1824.9000242
 
0.1%
1816.5500492
 
0.1%
1809.4500123
0.1%
1808.3000497
0.3%
1807.5499881
 
< 0.1%
1806.1000371
 
< 0.1%
2026-02-01T18:39:42.022485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

BOP
Real number (ℝ)

Zeros 

Distinct1975
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.0023850324
Minimum-2.7037707
Maximum2.7627087
Zeros258
Zeros (%)10.7%
Negative1078
Negative (%)44.7%
Memory size37.7 KiB
2026-02-01T18:39:43.354671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2.7037707
5-th percentile-0.94942706
Q1-0.52546209
median0
Q30.51035496
95-th percentile0.9380069
Maximum2.7627087
Range5.4664794
Interquartile range (IQR)1.035817

Descriptive statistics

Standard deviation0.60119757
Coefficient of variation (CV)-252.07102
Kurtosis-0.63483285
Mean-0.0023850324
Median Absolute Deviation (MAD)0.52106125
Skewness0.04036185
Sum-5.7479282
Variance0.36143852
MonotonicityNot monotonic
2026-02-01T18:39:43.434633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0258
 
10.7%
-178
 
3.2%
174
 
3.1%
-0.54
 
0.2%
-0.66666666673
 
0.1%
0.73643271482
 
0.1%
-0.58461350662
 
0.1%
-0.50413123092
 
0.1%
0.24999788072
 
0.1%
0.52
 
0.1%
Other values (1965)1983
82.3%
ValueCountFrequency (%)
-2.7037706851
 
< 0.1%
-1.7407541371
 
< 0.1%
-1.2394788511
 
< 0.1%
-1.1430066271
 
< 0.1%
-1.0520828041
 
< 0.1%
-178
3.2%
-0.99742016671
 
< 0.1%
-0.9953282491
 
< 0.1%
-0.99459591431
 
< 0.1%
-0.99390393681
 
< 0.1%
ValueCountFrequency (%)
2.7627087081
 
< 0.1%
2.7500127161
 
< 0.1%
1.6327673491
 
< 0.1%
1.2631384521
 
< 0.1%
1.0583979331
 
< 0.1%
1.0430137171
 
< 0.1%
174
3.1%
0.99651652421
 
< 0.1%
0.99617948941
 
< 0.1%
0.99615478521
 
< 0.1%

CMO
Numeric time series

High correlation 

Distinct2407
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6005636
Minimum-73.147026
Maximum80.217411
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:43.543739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-73.147026
5-th percentile-48.086638
Q1-17.919796
median1.9558174
Q323.70772
95-th percentile52.738509
Maximum80.217411
Range153.36444
Interquartile range (IQR)41.627516

Descriptive statistics

Standard deviation29.973241
Coefficient of variation (CV)11.525671
Kurtosis-0.50782857
Mean2.6005636
Median Absolute Deviation (MAD)20.654515
Skewness0.00050734213
Sum6267.3583
Variance898.39518
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value9.454947085 × 10-18
2026-02-01T18:39:43.664076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:43.960076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:44.839707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
32.565613512
 
0.1%
-21.500955532
 
0.1%
-32.947674962
 
0.1%
1.2832233921
 
< 0.1%
6.6202012321
 
< 0.1%
6.3363732511
 
< 0.1%
23.714815911
 
< 0.1%
33.03742311
 
< 0.1%
35.723019831
 
< 0.1%
44.261049951
 
< 0.1%
Other values (2397)2397
99.5%
ValueCountFrequency (%)
-73.147025691
< 0.1%
-70.795306891
< 0.1%
-69.818961521
< 0.1%
-68.806409991
< 0.1%
-68.743650261
< 0.1%
-67.080172481
< 0.1%
-66.992859581
< 0.1%
-66.493095991
< 0.1%
-66.282531711
< 0.1%
-66.141021531
< 0.1%
ValueCountFrequency (%)
80.217411441
< 0.1%
78.551546841
< 0.1%
77.79128721
< 0.1%
76.202726991
< 0.1%
76.150757461
< 0.1%
76.046773221
< 0.1%
73.383234271
< 0.1%
72.447394091
< 0.1%
72.226940911
< 0.1%
71.123796931
< 0.1%
2026-02-01T18:39:43.746549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MFI
Numeric time series

Distinct2409
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.082793
Minimum-1.0555854 × 10-13
Maximum100
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:45.319009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1.0555854 × 10-13
5-th percentile1.5297483
Q123.851568
median44.791812
Q370.346482
95-th percentile98.730093
Maximum100
Range100
Interquartile range (IQR)46.494914

Descriptive statistics

Standard deviation29.732118
Coefficient of variation (CV)0.63148586
Kurtosis-1.0297891
Mean47.082793
Median Absolute Deviation (MAD)22.915847
Skewness0.14993581
Sum113469.53
Variance883.99884
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value1.215006197 × 10-13
2026-02-01T18:39:45.414918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:45.645994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:46.233119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
31.635827042
 
0.1%
74.095583691
 
< 0.1%
74.199257461
 
< 0.1%
74.127355681
 
< 0.1%
74.170952471
 
< 0.1%
74.226471741
 
< 0.1%
74.260537061
 
< 0.1%
74.307546011
 
< 0.1%
73.922961061
 
< 0.1%
74.3834251
 
< 0.1%
Other values (2399)2399
99.5%
ValueCountFrequency (%)
-1.055585375 × 10-131
< 0.1%
-8.486371619 × 10-141
< 0.1%
0.019787391561
< 0.1%
0.020094224411
< 0.1%
0.021970898191
< 0.1%
0.022009341871
< 0.1%
0.02239488311
< 0.1%
0.022489537691
< 0.1%
0.024150298511
< 0.1%
0.035429027161
< 0.1%
ValueCountFrequency (%)
1001
< 0.1%
1001
< 0.1%
1001
< 0.1%
99.989248641
< 0.1%
99.989209621
< 0.1%
99.988913511
< 0.1%
99.988757661
< 0.1%
99.988674521
< 0.1%
99.988443351
< 0.1%
99.98803351
< 0.1%
2026-02-01T18:39:45.497477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ROC
Numeric time series

High correlation 

Distinct2408
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17111858
Minimum-14.962502
Maximum12.136097
Zeros2
Zeros (%)0.1%
Memory size37.7 KiB
2026-02-01T18:39:46.826616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-14.962502
5-th percentile-4.8709027
Q1-1.6410858
median0.2430142
Q32.1162971
95-th percentile5.0247534
Maximum12.136097
Range27.098599
Interquartile range (IQR)3.7573829

Descriptive statistics

Standard deviation3.082077
Coefficient of variation (CV)18.011352
Kurtosis1.2655161
Mean0.17111858
Median Absolute Deviation (MAD)1.8799461
Skewness-0.28771898
Sum412.39579
Variance9.4991984
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value4.948709023 × 10-16
2026-02-01T18:39:46.930161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:47.182006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:47.834253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
02
 
0.1%
0.022796599242
 
0.1%
-1.1242207091
 
< 0.1%
-0.53552484231
 
< 0.1%
2.5144457481
 
< 0.1%
3.8169146851
 
< 0.1%
4.3684984751
 
< 0.1%
5.8164419791
 
< 0.1%
5.8281135921
 
< 0.1%
6.0978647521
 
< 0.1%
Other values (2398)2398
99.5%
ValueCountFrequency (%)
-14.962501531
< 0.1%
-12.06445661
< 0.1%
-12.011714541
< 0.1%
-11.954792061
< 0.1%
-11.791640891
< 0.1%
-11.785482181
< 0.1%
-11.653978131
< 0.1%
-11.432015541
< 0.1%
-11.362761241
< 0.1%
-11.196569231
< 0.1%
ValueCountFrequency (%)
12.136097141
< 0.1%
11.859093921
< 0.1%
10.990679731
< 0.1%
10.437376041
< 0.1%
10.297216651
< 0.1%
9.8236975031
< 0.1%
9.4484722661
< 0.1%
8.5571592611
< 0.1%
8.4311303271
< 0.1%
8.4044837321
< 0.1%
2026-02-01T18:39:47.015130image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WILLR
Numeric time series

High correlation  Zeros 

Distinct2319
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-47.616907
Minimum-100
Maximum8.8327657
Zeros43
Zeros (%)1.8%
Memory size37.7 KiB
2026-02-01T18:39:48.228537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-96.03435
Q1-77.309492
median-46.139083
Q3-16.481451
95-th percentile-2.3668928
Maximum8.8327657
Range108.83277
Interquartile range (IQR)60.828041

Descriptive statistics

Standard deviation32.083194
Coefficient of variation (CV)-0.67377738
Kurtosis-1.3851864
Mean-47.616907
Median Absolute Deviation (MAD)30.328977
Skewness-0.07561511
Sum-114756.74
Variance1029.3314
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value5.876136886 × 10-24
2026-02-01T18:39:48.478593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:48.744291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:49.405429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-043
 
1.8%
-10040
 
1.7%
-1002
 
0.1%
-23.088163492
 
0.1%
-85.955094712
 
0.1%
-79.054898872
 
0.1%
-14.615572422
 
0.1%
-75.510204082
 
0.1%
-12.184726332
 
0.1%
-25.303271992
 
0.1%
Other values (2309)2311
95.9%
ValueCountFrequency (%)
-1002
 
0.1%
-10040
1.7%
-1001
 
< 0.1%
-99.850559721
 
< 0.1%
-99.839008661
 
< 0.1%
-99.835566271
 
< 0.1%
-99.591214271
 
< 0.1%
-99.572916671
 
< 0.1%
-99.56412951
 
< 0.1%
-99.542096551
 
< 0.1%
ValueCountFrequency (%)
8.8327656621
 
< 0.1%
1.8109160931
 
< 0.1%
-043
1.8%
-0.11296676381
 
< 0.1%
-0.16662597661
 
< 0.1%
-0.17508866671
 
< 0.1%
-0.17981228391
 
< 0.1%
-0.22697830971
 
< 0.1%
-0.23089023831
 
< 0.1%
-0.31418725461
 
< 0.1%
2026-02-01T18:39:48.567742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

AD
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2256
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-455276.97
Minimum-1234611.5
Maximum602582.62
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:49.919587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1234611.5
5-th percentile-1060785.4
Q1-809254.59
median-411440.77
Q3-43028.512
95-th percentile130231.4
Maximum602582.62
Range1837194.1
Interquartile range (IQR)766226.08

Descriptive statistics

Standard deviation419574.18
Coefficient of variation (CV)-0.92158006
Kurtosis-0.8384124
Mean-455276.97
Median Absolute Deviation (MAD)387129.2
Skewness0.044069327
Sum-1.0972175 × 109
Variance1.760425 × 1011
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4862395884
2026-02-01T18:39:50.018069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:50.272085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:50.951413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-283378.10188
 
0.3%
-435654.2856
 
0.2%
-406646.41755
 
0.2%
-3775.0758834
 
0.2%
-413454.47184
 
0.2%
-669727.774
 
0.2%
-502.36464784
 
0.2%
-484.28853993
 
0.1%
-669731.773
 
0.1%
-608439.44883
 
0.1%
Other values (2246)2366
98.2%
ValueCountFrequency (%)
-1234611.5291
< 0.1%
-1231919.1761
< 0.1%
-1230671.8131
< 0.1%
-1230380.1541
< 0.1%
-1230376.421
< 0.1%
-1230128.8721
< 0.1%
-1230115.9971
< 0.1%
-1229927.0861
< 0.1%
-1229614.8421
< 0.1%
-1229505.4321
< 0.1%
ValueCountFrequency (%)
602582.61861
< 0.1%
602414.22261
< 0.1%
602361.17191
< 0.1%
602341.17441
< 0.1%
602314.64121
< 0.1%
602214.54711
< 0.1%
601905.25811
< 0.1%
601888.07121
< 0.1%
601859.59811
< 0.1%
601784.59811
< 0.1%
2026-02-01T18:39:50.099761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

OBV
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct2316
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-894981.45
Minimum-2560065
Maximum249125
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:51.501516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2560065
5-th percentile-2282014.6
Q1-1566746.8
median-600251.5
Q3-178741.75
95-th percentile213966.9
Maximum249125
Range2809190
Interquartile range (IQR)1388005

Descriptive statistics

Standard deviation814177.56
Coefficient of variation (CV)-0.90971445
Kurtosis-1.1883313
Mean-894981.45
Median Absolute Deviation (MAD)604391
Skewness-0.38004736
Sum-2.1569053 × 109
Variance6.6288509 × 1011
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.7611205035
2026-02-01T18:39:51.601784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:51.862697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:52.518287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-25371696
 
0.2%
-22822324
 
0.2%
-2292753
 
0.1%
-25587433
 
0.1%
-25587483
 
0.1%
-22218823
 
0.1%
-18788533
 
0.1%
-19888553
 
0.1%
-22218812
 
0.1%
-4449542
 
0.1%
Other values (2306)2378
98.7%
ValueCountFrequency (%)
-25600651
< 0.1%
-25600561
< 0.1%
-25599521
< 0.1%
-25598491
< 0.1%
-25598151
< 0.1%
-25597281
< 0.1%
-25595481
< 0.1%
-25593531
< 0.1%
-25592771
< 0.1%
-25589781
< 0.1%
ValueCountFrequency (%)
2491251
< 0.1%
2490911
< 0.1%
2490481
< 0.1%
2490451
< 0.1%
2490192
0.1%
2490011
< 0.1%
2489821
< 0.1%
2489641
< 0.1%
2489551
< 0.1%
2489091
< 0.1%
2026-02-01T18:39:51.686327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

NATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1825841
Minimum0.50183061
Maximum3.3283981
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:52.935833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.50183061
5-th percentile0.66059166
Q10.87802485
median1.1227111
Q31.3817588
95-th percentile1.932455
Maximum3.3283981
Range2.8265675
Interquartile range (IQR)0.50373393

Descriptive statistics

Standard deviation0.41686924
Coefficient of variation (CV)0.35250705
Kurtosis2.4708718
Mean1.1825841
Median Absolute Deviation (MAD)0.25086123
Skewness1.274142
Sum2850.0277
Variance0.17377996
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0007040159619
2026-02-01T18:39:53.200399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:53.449695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:54.168286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.4614175091
 
< 0.1%
1.462848031
 
< 0.1%
1.5076769381
 
< 0.1%
1.508267241
 
< 0.1%
1.5708007271
 
< 0.1%
1.5584816481
 
< 0.1%
1.559732961
 
< 0.1%
1.867425241
 
< 0.1%
1.9090198941
 
< 0.1%
1.8922992891
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
0.50183061131
< 0.1%
0.51547229271
< 0.1%
0.51746194231
< 0.1%
0.52288357981
< 0.1%
0.54037974721
< 0.1%
0.54354629561
< 0.1%
0.54356907361
< 0.1%
0.55413798041
< 0.1%
0.55581830371
< 0.1%
0.55736882651
< 0.1%
ValueCountFrequency (%)
3.3283981371
< 0.1%
3.2973362941
< 0.1%
3.1426837341
< 0.1%
3.1294392441
< 0.1%
3.1231140871
< 0.1%
3.0498946961
< 0.1%
3.02350741
< 0.1%
3.018984571
< 0.1%
2.9214454571
< 0.1%
2.8860986061
< 0.1%
2026-02-01T18:39:53.283155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.065297
Minimum6.4264427
Maximum54.425832
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:54.530428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum6.4264427
5-th percentile8.3676496
Q111.326465
median14.83974
Q318.424947
95-th percentile29.433613
Maximum54.425832
Range47.999389
Interquartile range (IQR)7.0984819

Descriptive statistics

Standard deviation6.9391603
Coefficient of variation (CV)0.43193476
Kurtosis5.2749594
Mean16.065297
Median Absolute Deviation (MAD)3.5355933
Skewness1.8981636
Sum38717.366
Variance48.151945
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.004233146172
2026-02-01T18:39:54.741091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:55.022773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:55.796959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
16.044903191
 
< 0.1%
15.863124391
 
< 0.1%
16.337186931
 
< 0.1%
16.334534211
 
< 0.1%
17.34635321
 
< 0.1%
17.414474311
 
< 0.1%
17.334872491
 
< 0.1%
19.83952621
 
< 0.1%
20.086706391
 
< 0.1%
20.166232591
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
6.4264426861
< 0.1%
6.6054016931
< 0.1%
6.6135095161
< 0.1%
6.6594451441
< 0.1%
6.7345073861
< 0.1%
6.7910079541
< 0.1%
6.9476621451
< 0.1%
6.9837757231
< 0.1%
6.9959842381
< 0.1%
7.0441624121
< 0.1%
ValueCountFrequency (%)
54.425832061
< 0.1%
53.004740341
< 0.1%
50.744912721
< 0.1%
50.581128021
< 0.1%
50.453908081
< 0.1%
50.027424181
< 0.1%
49.435872331
< 0.1%
48.992914651
< 0.1%
48.379136771
< 0.1%
48.122912441
< 0.1%
2026-02-01T18:39:54.857256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

TRANGE
Real number (ℝ)

High correlation 

Distinct648
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.075477
Minimum0.099975586
Maximum163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:56.425649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.099975586
5-th percentile3.7000732
Q18.3000488
median13.099976
Q320.274963
95-th percentile38.154962
Maximum163
Range162.90002
Interquartile range (IQR)11.974915

Descriptive statistics

Standard deviation12.479958
Coefficient of variation (CV)0.77633515
Kurtosis18.037362
Mean16.075477
Median Absolute Deviation (MAD)5.5
Skewness3.0354281
Sum38741.9
Variance155.74935
MonotonicityNot monotonic
2026-02-01T18:39:56.506803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.518
 
0.7%
917
 
0.7%
817
 
0.7%
14.4000244116
 
0.7%
11.3000488316
 
0.7%
1016
 
0.7%
11.515
 
0.6%
515
 
0.6%
1415
 
0.6%
7.09997558615
 
0.6%
Other values (638)2250
93.4%
ValueCountFrequency (%)
0.099975585943
0.1%
0.19995117193
0.1%
0.30004882812
 
0.1%
0.39990234382
 
0.1%
0.59997558595
0.2%
0.69995117192
 
0.1%
0.80004882812
 
0.1%
0.89990234381
 
< 0.1%
0.90002441411
 
< 0.1%
13
0.1%
ValueCountFrequency (%)
1631
< 0.1%
121.40002441
< 0.1%
105.20007321
< 0.1%
102.89990231
< 0.1%
101.90002441
< 0.1%
99.400024411
< 0.1%
98.199951171
< 0.1%
94.099975591
< 0.1%
84.700073241
< 0.1%
84.51
< 0.1%

TSF
Numeric time series

High correlation  Non stationary  Unique 

Distinct2410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1343.1491
Minimum1056.7846
Maximum1888.4583
Zeros0
Zeros (%)0.0%
Memory size37.7 KiB
2026-02-01T18:39:56.606689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1056.7846
5-th percentile1119.7434
Q11220.8973
median1291.4956
Q31407.2948
95-th percentile1720.5635
Maximum1888.4583
Range831.67364
Interquartile range (IQR)186.39747

Descriptive statistics

Standard deviation181.15437
Coefficient of variation (CV)0.13487286
Kurtosis0.096885649
Mean1343.1491
Median Absolute Deviation (MAD)81.956585
Skewness0.98472909
Sum3236989.4
Variance32816.905
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4087845572
2026-02-01T18:39:56.698494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T18:39:56.940083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps500
min3 days
max5 days
mean3 days, 3 hours and 12 minutes
std8 hours, 19 minutes and 25.61 seconds
2026-02-01T18:39:57.702514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1094.5450331
 
< 0.1%
1085.4252721
 
< 0.1%
1077.282411
 
< 0.1%
1071.4966951
 
< 0.1%
1075.8142881
 
< 0.1%
1081.5714451
 
< 0.1%
1087.3121181
 
< 0.1%
1080.9670681
 
< 0.1%
1072.1538641
 
< 0.1%
1071.4538431
 
< 0.1%
Other values (2400)2400
99.6%
ValueCountFrequency (%)
1056.7846091
< 0.1%
1057.5472571
< 0.1%
1057.9263811
< 0.1%
1057.9384581
< 0.1%
1058.3054961
< 0.1%
1058.9494371
< 0.1%
1060.772561
< 0.1%
1061.1384591
< 0.1%
1061.1824091
< 0.1%
1061.4439861
< 0.1%
ValueCountFrequency (%)
1888.4582521
< 0.1%
1875.1977941
< 0.1%
1864.2560381
< 0.1%
1863.530791
< 0.1%
1855.9879111
< 0.1%
1852.8483671
< 0.1%
1850.5263731
< 0.1%
1848.8956081
< 0.1%
1839.4857081
< 0.1%
1838.5296561
< 0.1%
2026-02-01T18:39:56.777794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-01T18:39:32.069875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.484954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.446676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.696577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.850009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.941391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.137043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.210256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.389065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.489741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.492583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.619721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.653120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.899907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.952785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.087204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.070118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.113859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.535273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.504112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.788397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.910617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.995389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.196416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.260065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.448116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.543882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.545643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.677414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.710086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.973420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.008869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.139380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.127642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.167069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.593218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.569658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.874138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.977667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.056311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.261370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.320358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.516888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.605374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.720830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.739895image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.776829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.035389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.070101image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.199631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.195404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.218442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.651108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.633801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.938765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.043061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.114055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.325938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.381172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.584485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.669496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.783969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.803689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.864627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.098614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.133321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.260391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.259365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.272823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.708487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.701966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.003613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.108164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.289731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.393639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.444071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.652628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.732655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.846355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.865882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.937977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.161433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.194614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.322516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.323521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.325209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.767449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.764974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.070956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.173490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.374197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.458575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.504285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.719411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.795940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.908822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.927512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.007930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.225546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.255947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.381664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.385497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.380491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.825245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.830742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.137522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.240521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.439743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.524751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.567327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.787892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.859254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.970588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.991742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.077986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.290297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.321084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.443834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.447999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.430299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.880405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.892763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.203403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.303741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.503745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.587174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.631871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.850184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.917774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.028938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.048992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.141755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.350533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.379040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.498857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.506125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.484819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.939936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.963193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.272835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.371974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.570001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.655272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.693723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.917457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.978759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.090744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.112553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.320714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.414382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.443820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.562440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.568662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.638887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:14.994793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.024540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.337143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.433738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.632406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.716319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.769433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.978917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.036611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.148856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.169215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.384902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.474401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.501986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.617982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.624353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.692702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.048974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.087707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.400876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.498881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.694274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.779306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.826932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.043247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.093082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.204679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.230316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.448976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.532921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.562415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.675917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.681954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.747537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.104014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.151460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.464880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.561573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.756743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.842867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.991540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.104691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.147975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.262116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.287955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.512999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.592733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.619963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.732931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.738611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.813522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.165954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.223547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.531167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.631077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.823645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.908087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.057070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.173351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.209707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.327450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.353194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.579377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.656547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.686141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.792933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.801786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.886896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.223010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.288593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.596075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.696019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.887039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.971588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.120717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.237254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.266665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.386200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.414018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.643355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.713747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.744818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.852002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.858557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.941605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.280795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.353006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.657797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.757127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:19.948967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.031825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.185601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.302457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.324403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.445319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.474998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.708845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.774749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.802357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.905432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.913675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.995111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.333624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.414403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.719940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.818323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.010316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.090715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.271385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.361824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.379266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.501199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.531433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.769456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.830899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.860554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:30.957801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.963852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:33.054024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:15.393229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:16.611379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:17.788025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:18.884377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:20.077095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:21.153593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:22.333417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:23.430510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:24.440645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:25.565004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:26.597838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:27.838398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:28.896972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:29.922139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:31.016763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T18:39:32.019820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T18:39:58.155718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ADATRBOPCMOEMAKAMAMAMFIMidPriceNATROBVROCTRANGETSFWILLRWMAclose
AD1.0000.3080.0530.1620.5770.5780.5740.1610.5710.1080.5380.0960.1780.5760.1440.5770.580
ATR0.3081.0000.0210.0060.4430.4450.4440.0940.4410.9260.5720.0030.5760.4350.0080.4420.436
BOP0.0530.0211.0000.3300.0270.0250.0200.0660.022-0.0040.0460.2570.0240.0390.3880.0280.083
CMO0.1620.0060.3301.0000.0910.0790.0750.3750.072-0.0630.0630.8670.0410.1920.9120.1140.205
EMA0.5770.4430.0270.0911.0000.9980.9990.0910.9980.1150.3410.0460.2510.9880.0490.9990.989
KAMA0.5780.4450.0250.0790.9981.0000.9970.0850.9960.1190.3490.0350.2520.9860.0360.9970.986
MA0.5740.4440.0200.0750.9990.9971.0000.0900.9990.1170.3390.0280.2510.9860.0290.9980.985
MFI0.1610.0940.0660.3750.0910.0850.0901.0000.0860.0530.1520.3010.0580.1450.3230.1050.132
MidPrice0.5710.4410.0220.0720.9980.9960.9990.0861.0000.1140.3350.0190.2490.9830.0220.9970.984
NATR0.1080.926-0.004-0.0630.1150.1190.1170.0530.1141.0000.482-0.0460.5450.106-0.0520.1130.105
OBV0.5380.5720.0460.0630.3410.3490.3390.1520.3350.4821.0000.0340.2940.3360.0780.3400.339
ROC0.0960.0030.2570.8670.0460.0350.0280.3010.019-0.0460.0341.0000.0380.1570.8700.0700.152
TRANGE0.1780.5760.0240.0410.2510.2520.2510.0580.2490.5450.2940.0381.0000.2510.0230.2520.250
TSF0.5760.4350.0390.1920.9880.9860.9860.1450.9830.1060.3360.1570.2511.0000.1440.9930.992
WILLR0.1440.0080.3880.9120.0490.0360.0290.3230.022-0.0520.0780.8700.0230.1441.0000.0680.165
WMA0.5770.4420.0280.1140.9990.9970.9980.1050.9970.1130.3400.0700.2520.9930.0681.0000.991
close0.5800.4360.0830.2050.9890.9860.9850.1320.9840.1050.3390.1520.2500.9920.1650.9911.000

Missing values

2026-02-01T18:39:33.149010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T18:39:33.240459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DatecloseMAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2010-01-262010-01-261097.9000241117.4999881111.4576791120.6544041108.9181641120.0999760.000000-14.69978364.341830-4.588505-80.946248502.508257662.01.46141816.0449032.7000731094.545033
2010-01-272010-01-271084.4000241113.0499881106.5381061117.1369871102.8999891114.4500120.000000-25.7475340.175818-3.941890-98.209686502.508257-206032.01.46284815.86312413.5000001085.425272
2010-01-282010-01-281083.5999761107.7699831102.3675371112.3747011097.5454411109.549988-0.186670-26.3754280.118218-4.646256-88.181790-7141.076639-307200.01.50767716.33718722.5000001077.282410
2010-01-292010-01-291083.0000001101.8099851098.8461661106.7503071093.0418081106.449951-0.122699-26.8905660.096377-5.216172-88.863581-6649.136970-318656.01.50826716.33453416.3000491071.496695
2010-02-012010-02-011104.3000491099.2299931099.8377811106.6396911093.4945471106.4499510.7639360.5558070.806533-2.282977-62.976074-4679.497626-316204.01.57080117.34635330.5000001075.814288
2010-02-022010-02-021117.4000241097.0000001103.0309161107.0211201096.7981891103.0999760.00000013.3617791.845782-1.956649-39.202161-1753.334679-312878.01.55848217.41447418.3000491081.571445
2010-02-032010-02-031111.4000241096.9099981104.5525721107.0430321099.4163751099.049988-0.2699396.3895702.109863-0.080916-47.455248-2313.275232-313731.01.55973317.33487216.3000491087.312118
2010-02-042010-02-041062.4000241092.8800051096.8884731104.1093721093.1418351091.950012-0.920697-31.7180602.075298-3.654659-95.786832-3551.714714-315157.01.86742519.83952652.4000241080.967068
2010-02-052010-02-051052.1999511089.1800051088.7632871100.9844341085.7454611085.0499880.000000-36.9422182.063641-3.396989-92.592593-4332.438207-317113.01.90902020.08670623.3000491072.153864
2010-02-082010-02-081065.6999511086.2300051084.5699531099.5670371081.4763611085.0499880.000000-23.0928142.217049-2.693572-76.651494-4499.933583-316564.01.89229920.16623321.2000731071.453843
DatecloseMAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2019-08-132019-08-131502.1999511473.8699951479.0747971481.9356391489.0054491466.150024-0.17190953.28552725.8243375.070994-22.375535-209982.224260-1736356.01.36746020.54197847.7000731522.081311
2019-08-142019-08-141515.9000241482.8500001485.7702931490.0115521496.6472721466.1500240.67659759.87159125.9080946.296897-11.877395-209782.632089-1736028.01.36903920.75326523.5000001530.593413
2019-08-152019-08-151519.5999761492.7199951491.9211451498.4830001503.3290861481.850037-0.01653561.50036825.9290936.946298-9.042183-209740.210340-1735941.01.32503120.13517312.0999761537.608794
2019-08-162019-08-161512.5000001499.4099981495.6627551501.1367321506.9254511485.900024-0.60803848.63699191.2959004.627838-14.482777-210132.389109-1737756.01.33014120.11837719.9000241539.456047
2019-08-192019-08-191500.4000241502.9900021496.5240761501.0805011507.1054551494.549988-0.46258229.15716443.8954222.444357-23.754789-210128.204740-1737961.01.33840020.08134819.5999761536.559345
2019-08-202019-08-201504.5999761506.2099981497.9924221501.3220221507.3981781502.2999880.82558132.56561459.3187312.186902-20.536436-209811.740105-1737475.01.28015819.2612508.5999761531.898895
2019-08-212019-08-211504.5999761505.9399901499.1937951501.3486921507.1054471507.549988-0.04839532.56561476.637869-0.179133-27.043446-209506.904508-1737475.01.21815118.3283006.1999511523.736256
2019-08-222019-08-221497.3000491505.9000001498.8494781501.3297151505.5345481507.5499880.62859220.16021264.207443-0.026701-37.472501-208820.904508-1738161.01.18817617.79055910.7999271515.071433
2019-08-232019-08-231526.5999761508.9000001503.8950231503.1316551509.2981801507.5499880.97067443.66910364.2708272.004544-6.512950-207895.558508-1737178.01.24168218.95551734.0999761516.414278
2019-08-262019-08-261526.3000491511.0000001507.9686641504.2633871512.4618251513.500000-0.88946943.18955763.7504551.395071-24.251036-208159.242719-1737512.01.24213418.95869519.0000001516.998912